IBM likes to put the word "smarter" in front of just about everything, so it shouldn't come as much of a surprise that there is now a smarter storage initiative. But what may come as a pleasant surprise is that the initiative includes the ability to compress data in real time, resulting in as much as a five-fold increase of effective storage capacity.
According to David Gelardi, vice president of the Competitive Lab at IBM, the Storwize V7000 and System Volume Controller (SVC) systems can now compress active data by as much as 80 percent. In contrast, Gelardi says rival systems only compress data that is not being actively used.
In an era where the amount of data that needs to be managed is spiraling out of control, advances in compression technologies level the data storage playing field. Rather than having to invest in a massive number of storage systems, compression technology significantly increases the utilization rates of storage systems that today are notoriously abysmal.
IBM acquired Storwize in 2010 to gain access to that technology. Subsequently, Storwize became a brand that IBM is applying across a range of its storage systems. In addition to enhancing its data compression technology, IBM also added four-way clustering support for Storwize V7000 block systems that doubles the maximum system capacity to 960 drives to achieve 1.4 petabytes of storage. IBM also announced that its storage systems are now integrated with the high-performance computing systems from Platform Computing, which IBM acquired earlier this year.
To help better manage these environments from a storage perspective, IBM also announced that the IBM Tivoli Storage Productivity Center (TPC) suite has now been integrated with IBM Cognos business intelligence software in order to allow IT organizations to more easily create reports on storage consumption.
As storage consumes an ever-increasing amount of the IT budget, the need for more sophisticated approaches to managing storage has never been more apparent, especially with the rise of Big Data.